This material is brought to you by the Journals at AIS Electronic Library (AISeL). It has been accepted for inclusion in Communications of the Association for Information Systems by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact elibrary@aisnet.org.

A Descriptive Literature Review and Classification of Cloud Computing Research

Haibo Yang School of Information Management, Victoria University of Wellington Haibo.Yang@vuw.ac.nz

Mary Tate School of Information Management, Victoria University of Wellington

We present a descriptive literature review and classification scheme for cloud computing research. This includes 205 refereed journal articles published since the inception of cloud computing research. The articles are classified based on a scheme that consists of four main categories: technological issues, business issues, domains and applications, and conceptualising cloud computing. The results show that although current research is still skewed towards technological issues, new research themes regarding social and organisational implications are emerging. This review provides a reference source and classification scheme for IS researchers interested in cloud computing, and to indicate under-researched areas as well as future directions. Keywords: cloud computing, descriptive literature review, classification Editor’s Note: The article was handled by the Department Editors for Information Technology and Systems.

Volume 31, Article 2, pp. 35-60, July 2012

Volume 31

Article 2

Such appealing promises have made cloud computing a dominant IT press topic over the past three years. etc. p. A traditional way for enterprises to process their data is to use the computing power provided by their own in-house data centres. The NIST further suggests that a cloud computing model should be composed of five essential characteristics. 1998]. Then we discuss the implications of this review. electricity. and how it can be distinguished from related concepts such as grid computing. This vision is not essentially new. computer networks are still in their infancy. 2009]. Leonard Kleinrock. some suggestions as to where more effort should be focused in the future in order to produce more ’consumable research’ [Robey and Markus. the NIST definition of cloud computing is adopted to facilitate the following discussions. and Brandic. Yeo. and finally offer some conclusions.
II. where it is today. as needed automatically without requiring human interaction each service’s provider. ‘Cloud computing’. INTRODUCTION
In an age of information and globalisation. It promises to provide on-demand computing power with quick implementation. Cloud computing has been cited as ‘the fifth utility’ (along with water. Ideally. a cloud should have all of the five following characteristics: 1.) in late 2006. The present paper aims to assess the state of cloud computing research. For the purpose of this study.com. Among the various definitions. 2009]. Cloud Computing regularly appears in the ‘top 10’ current issues for CIOs identified by industry commentators such as the VP and editor in chief of Information Week [Preston. LITERATURE REVIEW
This section offers a short introduction to what cloud computing is. and most importantly. as a term for Internet-based computing service. one of the chief scientists of the original Advanced Research Projects Agency Network (ARPANET) project which seeded the Internet. 4]. Research
Volume 31 36
Article 2
. retired Stanford professor and Turing Award winner. predicted that in the future computing would become a ‘public utility’ [Wheeler and Waggener. It could be argued that cloud computing has begun to fulfil this vision of computing on demand. in his speech at MIT’s Centennial. A consumer can unilaterally provision computing capabilities. 2011]. IT cloud-service spending will grow from about USD16 billion in 2008 to about USD42 billion by 2012 [Leavitt. Broberg. will serve individual homes and offices across the country’ [Kleinrock.g.A Descriptive Literature Review and Classification of Cloud Computing Research
I. given the current relevance of the topic. Cloud computing offers an alternative. However operating a private data centre to keep up with rapidly growing data processing requests can be complicated and costly. In 1969. We portray a current landscape of this research stream. gas. The remainder of this article is organised as follows: First a brief overview of cloud computing is given. The relative novelty and rapidly increasing growth of cloud computing makes it an exciting area for research. and telephone) whereby computing services are readily available on demand. Dating back to 1961. On-demand self-service. we will probably see the spread of “computer utilities” which. was launched by industry giants (e. and consequently lower cost. three service levels. Next the research methodology and our classification schema are presented. John McCarthy. Attempts to define cloud computing have come from different perspectives within practice and academia (as listed in Table 1). The first step of studying research into cloud computing is to clarify the concept. massive computing power is desired to generate business insights and competitive advantage [Liu and Orban. 2009]. and four deployment models [Mell and Grance. like present electric and telephone utilities. 2009] as shown in Figure 1. the one by the NIST (National Institute of Standards and Technology) has gained recent recognition and popularity. like other utility services available in today’s society [Buyya. This is followed by the results of our literature review and classification. said: ‘As of now. low maintenance. 2005. Venugopal. As projected by market-research firm IDC. such as server time Descriptive Literature Review and Classification of with Cloud Computing and A network storage. Google. fewer IT staff. Amazon. but as they grow up and become sophisticated. 2008].

mobile phones. to quickly scale in and scale out. use of computing resources on a short-term basis as needed. Konwinski. and managed infrastructure capable of Forrester [Staten. A large pool of easily usable and accessible virtualised resources (such as [Vaquero. networking. 2010] 2. et al. hardware.g. and builds on virtualisation. 2008] distributed computing. Bittman. 2009] pool of configurable computing resources (e. highly scalable. Fox. A type of parallel and distributed system consisting of a collection of [Buyya et al. processing. grid computing. elimination of up-front commitments by cloud users.g. Smith. Cearley. and Web and software services. and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. laptops. Capabilities are available over the network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e. 3.. applications. Broad network access. Resource pooling. Examples of resources include storage..
Volume 31
Article 2
37
. Scott. the UC Berkeley [Armbrust. 2009] A pool of abstracted. allowing also for an optimum resource utilisation. provided as a service across the Internet to multiple external customers. Capabilities can be ‘elastically’ provisioned and released. Cloud Computing Anatomy [Adapted from Craig–Wood. memory. with different physical and virtual resources dynamically assigned and reassigned according to consumer demand. in some cases automatically. These resources can be Caceres. networks. and PDAs). 2009] Cloud computing embraces cyber-infrastructure. network bandwidth.Table 1: Definitions of Cloud Computing Definition Reference A style of computing where massively scalable IT-related capabilities are Gartner [Plummer.
Figure 1. Cappuccio. 2009] interconnected and virtualised computers that are dynamically provisioned and presented as one or more unified computing resources based on servicelevel agreements established through negotiation between the service provider and consumers. servers. A model for enabling convenient. and virtual machines. Katz.. 2009] dynamically reconfigured to adjust to a variable load (scale). on-demand network access to a shared NIST [Mell and Grance. Joseph. Rapid elasticity. Rodero–Merino. storage. development platforms and/or services). The illusion of infinite computing resources available on demand. and the ability to pay for Griffith. This pool of resources is typically exploited by a pay-per-use model in which guarantees are offered by the infrastructure provider by means of customised SLAs. 2008] hosting end-customer applications and billed by consumption. utility computing. and Lindner. [Vouk. 4. et al. The provider’s computing resources are pooled to serve multiple consumers using a multi tenant model.

is owned and operated by independent vendors and accessible to the general public. Differing from traditional hosting services with which physical servers or parts thereof are rented on a monthly or yearly basis. storage. Another example. test. on demand manner via the Internet [Leavitt. Some researchers suggest to further divide IaaS into HaaS (Hardware as a Service) and DaaS (Data as a Service) [Wang. Infrastructure as a Service (IaaS): IaaS provides the raw materials of cloud computing. based on an open source framework. or USD0. Raicu. Hybrid cloud is a combination of two or more types of clouds (private.12 per hour for a Windows one). and then release them as soon as the computational work is done. Public cloud. Cloud computing services are generally classified into three layers: 1. 2008]. and production environment) traditionally carried by the developers who can then concentrate on more productive problems. It may be managed by the organisations or a third party and may exist on premise or off premise. Karl. the cloud infrastructure is rented as virtual machines on a peruse basis and can scale in and out dynamically. processing. Youseff.. or storage). Some other appealing features of PaaS include built-in instruments measuring the usage of the deployed applications for billing purposes and an established online community for collaboration and problem solving. Platform as a Service (PaaS): PaaS moves one step further than IaaS by providing programming and execution environments to the user. host firewalls) [Mell and Grance. 2009]. The three service levels of cloud computing will be discussed in the following section.g. Other deployment models are variations of public cloud but share a similar set of technologies and levels of services. 2009]. from the interface design. Wolski. Kunze. and compliance considerations). and deploy platform. The PaaS user does not manage or control the underlying cloud infrastructure (including network. but has control over the deployed applications and possibly application hosting environment configurations [Mell and Grance. and in some cases limited control of select networking components (e. a user can easily access tens of thousands of virtual servers from EC2 to run a business analysis. 2008a]. but it is more common that IaaS is considered as a whole concept. public cloud is what the term ‘cloud computing’ was initiated for and commonly refers to. to process logic. an organisation may bridge its internally operated private cloud with other public clouds together by standardised or proprietary technology in order to satisfy business needs [Mell and Grance. storage and other forms of lower level network and hardware resources in a virtual. setting up and switching among development environment.g. or public). a cloud can be classified as: 1. to integration [Lawton. test environment. Castellanos. 2009]. 2009]. Depending on the relationship between the provider and the consumer. Private cloud is an internal utilisation of cloud technologies which is maintained in-house and solely accessible to internal users within an organisation. mission.
Volume 31 38
Article 2
. USD0. Such an approach can reduce most of the system administration burden (e. based on customer needs. A PaaS product acts as an integrated design. 2. Cloud systems automatically control and optimise resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e. community. 2008]. Such on-demand scalability is enabled by the recent advancements in virtualisation and network management. bandwidth.085 per hour for an on-demand small Linux/UNIX server instance. PaaS typically provides a complete set of development tools. and then directly deploy the applications onto the provider’s cloud infrastructure within a few clicks. and allows users to set up a cloud infrastructure on premise and experiment prior to purchasing commercial services [Foster. develop. Among the four deployment models. Typical IaaS examples are Amazon EC2 (Elastic Cloud Computing) and S3 (Simple Storage Service) where computing and storage infrastructure are open to public access in a utility fashion.g. Grzegorczyk. 2009]. Yong. Soman. 4. and active user accounts) [Mell and Grance. deployed applications. Tao. For example. servers. 3.g. Kramer.g. such as processing. Eucalyptus [Nurmi. and Lu. et al. operating systems. Community cloud is shared by several organisations and supports a specific community that has shared concerns (e. storage. Obertelli. 2009]. 2. security requirements. policy. For a fee (e. Measured Service. The PaaS user can create applications using programming languages and APIs supported by the provider. the one most commonly referred to. IaaS users do not need to manage or control the underlying cloud infrastructure but have control over operating systems. is a cloud implementation that provides a compatible interface to Amazon EC2.5.

Authentication and authorisation security policies are used to ensure the separation of user data. 2009].g. SaaS is expected to alleviate the user’s burden of software maintenance. 2011]. 2009].. 2010.
III. etc. RESEARCH METHODOLOGY
A Descriptive Literature Review
The literature review is an essential approach to conceptualise research areas and survey and synthesise prior research [Webster and Watson.
1 2 3
http://www. compared to the traditional scattered enterprise data centres [Katz. PaaS providers often intentionally cultivate online user communities 1 and marketplaces (e. Thus on its own website. Th is system provides users with complete CRM applications as well as a user side customisation platform based on its PaaS by-product Force. This figure was 82. 2002]. and reduce the expense of software purchases by on-demand pricing [Wang et al. SaaS providers also leverage the ‘power of crowd’ by providing online user communities and marketplaces where SaaS users and third-party vendors can share. 2008]. It is suggested that the lack of review articles has been hindering the progress of IS field [Webster and Watson. and sell their codes. http://appexchange. the other is ‘customise with code’ that allows developers to create new functionalities beyond the constraints of configuration. enabling non-programmer users to build their own online applications in the cloud. 3. Two types of customisations are available ―one is ‘point-and-click configuration’ that requires no coding. PaaS offerings lower the entry level for online application development.com/platform/customization (current 20 Apr.com/enterprise/marketplace http://www. sell. The new add-ons bought from the marketplace can be deployed by a few clicks in a few minutes. and SaaS are inherently interrelated with each building on the former. PaaS.salesforce. This approach can eliminate the need to install. WaveMaker. modules. An example of such a marketplace is 3 Salesforce. cloud computing has promised to bring low environmental cost and high energy efficiency. Some evidence shows that these are being delivered [Sultan. 2002].An example of PaaS is Google’s App Engine. reliability. and services to each other. provides an easy and intuitive way of building Java-based websites. From an environmental standpoint. Software as a Service (SaaS): SaaS provides users with complete turnkey applications through the Internet.com. or customisation services to enhance the core application. which enables users to build applications on the same scalable systems that power Google applications [Foster et al. and buy add-ons. A prominent example of SaaS is Salesforce.300 Salesforce implementations. and Martin. cloud computing can deliver on-demand computing power at a very low (or no) upfront cost for infrastructure and ongoing maintenance. 2008]. 2011). IaaS.400 in Dec. these seductive promises have attracted enormous interest from many organisations. Salesforce. products. Similar to PaaS.. This marketplace acts as a specialized aggregator and enables features such as requesting quotes.com’s online CRM system.salesforce. with Apex ―Salesforce. All in all. 2009].com’s AppExchange . and scalability [Erdogmus. Cloud computing also promises to provide better performance. recently acquired by VMware. Google’s App Engine aims to enable users to easily develop applications on the Internet in collaboration with other developers from around the world [Leavitt. even complex systems such as those for CRM or ERP [Leavitt. To facilitate collaboration. sharing demos. 1988]. run. Such a sharing mechanism enables the cost and price of SaaS to stay competitive compared to traditional off-the-shelf and bespoke software. SaaS is known for its multi-tenant architecture in which all the users share the same single code base maintained by the provider. and maintain the application on local computers. 2009].com’s own native programming language. These types of platforms comprise a modern instantiation of the End User Computing (EUC) paradigm which has long been envisioned by generations of IS researchers [Huff.com/home
Volume 31
Article 2
39
.com declares that there are currently ‘77. with considerable economies of scale. Software or applications are hosted as services in the cloud and delivered via browsers once subscribed to by the user. From an enterprise standpoint.google. buy. Google Apps Marketplace ) where developers can share. All of them 2 unique’ . Munro. Cloud computing has promised many technological and sociological benefits. These three layers reflect a full spectrum of cloud computing services. The computing power is generated from highly centralised and standardised data centres which contain up to several million servers. owing to the advanced electrical and cooling systems used by its centralised data centres. It directly contributes to a cumulative research culture.

In the meantime. research methodology. and the publication channels are still scattered. as this is a recent phenomenon which emerged only three years ago. focusing on theories and frameworks. focusing on limited outlets cannot be justified for a literature review on cloud computing. for a literature review on cloud computing. Often it is applied to generate insights from a series of experiments. 2005]. Jackson. filtering.
Figure 2. The procedure for conducting this descriptive review is described in the next section. Traditionally this is done by targeting some prominent journals and conferences. and classifying processes. thus this approach is vulnerable to subjectivity. The premise underlying this approach is that repeated results in the same direction across multiple studies. 2002]. Qualitative studies have to be excluded by a meta-analysis due to its extremely quantitative nature. 1987]. First a reviewer needs to conduct a comprehensive literature search to collect as many relevant papers as possible in an investigated area. Sabherwal. 2005]. often in the form of frequency analysis. 2005]. and ScienceDirect (Elsevier). These four review methods are placed in a qualitative-quantitative continuum to illustrate their different focuses [King and He. elementary factors and their research outcomes. Given the nascence of this research area. Then the reviewer treats an individual study as one data record and identifies trends and patterns among the papers surveyed [King and He. A descriptive review focuses on revealing an interpretable pattern from the existing literature [Guzzo et al. Vote Counting. it is appropriate and practical to focus on online databases rather than library collections. may be more powerful evidence than a single significant result [King and He. Vote counting is generally used to draw inferences about focal relationships by combining individual research findings [King and He.. 2005]. However. Descriptive Review. 2006]. Jeyaraj. such as publication time. and Chowa. 2005]. It is conducted by verbally describing the past studies. there is no standardised procedure for a narrative review. It is not uncommon for ‘two reviews to arrive at rather different conclusions from the same general body of literature’ [Guzzo. these four databases cover forty-four of the ISWorld’s top fifty
Volume 31 40
Article 2
. or theories. Meta-analysis aims at statistically providing support for a research topic by synthesising and analysing the quantitative results of many empirical studies [King and He. correlations.A literature review can be conducted in different ways. p. Four prominent online databases were targeted: General OneFile. The benefit of this approach is to generate a much less subjective literature review in a specific research context. and Katzell. it may specifically examine the relationships between certain Independent Variables (IVs) and Dependent Variables (DVs) derived from existing research findings. Therefore. The outcome of such a review is often claimed to be representative of the current state of a research domain. Petter and McLean. Literature Review Methods on a Qualitative–Quantitative Continuum The narrative review is the traditional way of reviewing the literature and is skewed towards a qualitative interpretation of the literature. even if some of them are nonsignificant. It produces some quantification. Only similar quantitative studies are collected for a meta-analysis. In most cases. 2005]. Here a tally is made of the frequency with which existing research findings support a particular proposition. 408]. Figure 2 shows four methods of literature review: Narrative Review. However. According to Levy and Ellis. 2009.
Scope of the Literature Search
The first step of a literature analysis study is to locate relevant literature through computer and manual searches. and research outcomes. 1999. ProQuest (ABI/INFORM). The conduct of a narrative review largely depends on the reviewer’s personal preference. Our objective is to portray a landscape of cloud computing as an emerging research area and provide a snapshot to guide future development. using online database searches as a primary literature collecting approach has become an emerging culture among IS researchers who are interested in contemporary phenomena [Hwang and Thorn. IEEE Xplore. and Meta-Analysis. Such a review method often has a systematic procedure including searching. This approach is relevant to other research topics like Electronic Commerce where some major publication outlets have been formed by the long development of the research area [Ngai and Wat.1987. with regard to a hypothesized relationship [King and He. we do not and could not aim at examining any variables. We found a descriptive review approach was most appropriate for the current stage of this research.

4
The remaining six journals―Communications of the Association for Information Systems. as in-depth reading of the articles was required to perform the filtering tasks. 262 articles were discarded. Journal of the Association for Information Systems. This classification was based on categorising the research focus of the 205 articles which remained after the filtering processes. This round of filtering excluded those articles that did not address the cloud computing phenomenon in business and technology. In this process. and ‘Nuclear Risks’. Moreover. In total 136 articles were discarded by the end of this round which resulted in 490 articles being retained in the EndNote database. The final round involved excluding articles from non-refereed journals. the ‘only journal’ option was selected in ScienceDirect and IEEE Xplore. and. and Informing Science―were then manually searched.
Volume 31
Article 2
41
.
Classification Scheme
To systematically reveal and examine academic insights on cloud computing.IS journals [Levy and Ellis.com was used for reconfirming that all articles included in this study were from peer-reviewed journals. we noticed the existence of non-refereed journals in the EndNote database during the first two rounds of filtering. This round was the most comprehensive and time-consuming phase. This first round of scanning also allowed the identification and exclusion of further duplicates not identified by EndNote due t o the misplacement of authors’ first names and surnames. ‘Atmospheric Sciences’. 2006]. and we therefore felt that these databases were comprehensive enough to produce a literature set that is representative of the current status of IS research. while they were not direct duplicates. The first step was an initial reading of the 205 papers. and Wilderom. including peer-reviewed’ option was selected in ProQuest. Furtmueller. These articles included irrelevant studies in ‘Meteorology’ . which resulted in 221 articles left in the EndNote database. some articles were identified in this round which. We conducted keyword and abstract searches across all the four databases and for all years (until 25 May 2011) with the phrase ‘cloud computing’. covered nearly the same contributions by the same group of authors. 2011]. Though ‘peer-reviewed’ and ‘scholarly’ filters were applied during the literature search. This step discarded sixteen non-refereed articles and resulted in the final 205 articles. Following a staged selection process [Dyba and Dingsoyr. ‘Geophysics’. Reading the abstracts and full texts also enabled us to exclude those book reviews. with a clear focus on cloud computing. the ‘scholarly journals. a literature classification scheme was developed. only the most recent paper was kept and the others were discarded. In such cases. Hence Ulrichsweb. Specific subcategories were assigned to each article and then synthesised into more generic top categories in three steps as described below. where necessary to explicate the content of the paper further. remained in the Endnote database for further analysis and classification. but instead merely mentioned cloud computing along with other technology phenomena for a general coverage. These 205 peer-reviewed academic articles. A ‘bottom-up’ approach informed by grounded theory [Glaser and Strauss. the remaining 626 articles in the database were then scanned and filtered in three rounds. The first round involved manually scanning titles for apparently irrelevant articles. briefs. 2008]. thirty to forty codes were identified. The second round involved manually scanning abstracts and reading full texts if necessary.
4
Filtering Process
The 735 articles were imported directly into an EndNote database. 1997]. The search aimed at peer -reviewed. scholarly journal articles. Human-Computer Interaction. They were mistakenly selected by the search engines. the ‘limited to peer-reviewed’ option was selected in General OneFile). therefore filters were used if available (e.g. Such an approach has recently been recommended as a rigorous method for reviewing literature [Wolfswinkel. Codes were generated from article keywords. International Journal of Electronic Commerce. and fifty articles without author names or written by anonymous authors were also discarded. The initial search resulted in 735 hits. Information Systems Journal. analysis of the article abstract. letters. Fifty-nine duplicates were automatically removed by using the ‘find duplication’ function of EndNote. we applied open coding techniques and generated a wide range of codes to capture the themes represented in each article [Strauss and Corbin. ‘Fluid Dynamics’. and technical news without adequate academic references and insights. 1967] was adopted to identify the categories used for this literature analysis. In the initial coding stages. careful reading of the entire article. By the end of this round. This round was to exclude those articles that did not address cloud computing as a central theme of discussion.

power conservation. et al. Dailey. 2009]. 2011]. we conducted an affinity workshop to negotiate and agree on the four broad research domains linking the twentyone detailed codes. 1993]. 1. 2011]. Berl. and Gepner. Warneke and Kao. 2011]. DeWitt. Sabala. Data Management: This subcategory includes specific issues associated with the large scale. Software Development: This subcategory represents a stream of software developer-oriented research. and Janecek. Domains and Applications. Tu. Dougherty. 2010. this subcategory includes articles exclusively targeting aspects such as service lifecycle in the cloud [Breiter and Behrendt. García–López. 2. 2011]. and Conceptualising Cloud Computing. de Meer.In the next stage. Rivard. However. This includes data consistency [Vogels. Bubak. Carrera. et al. Yang. Li.. algorithms for energy-aware scheduling are proposed [Mezmaz. Zomay. and environmental considerations in the design of data centres [Beloglazov. 2011]. and Talbot. Madden. 1997].. Zhan. Lin. Kessaci. and Herrera. was created. subtopics ‘Cloud Performance’. Consequently. Alham. to improve dynamic resource allocation [Streitberger and Eymann. Articles in this category are produced by researchers who see cloud computing as a white-box and are interested in its components and mechanisms. In order to derive the top level topics. This subcategory set was revised iteratively to make sure it was not only parsimonious but also represented the diversity of the initial coding. Melab. It is inevitable that a piece of research may contribute to several of the subcategories. di Girolamo. Gelenbe. et al. A: Technological Issues: This category focuses on technology details of cloud computing. Zhu. and Schmidt. Following the axial coding. ‘Data Centre Management’ were grouped into a higher level topic ‘Technical Issues’). 2009. White. 2009. 2011]. Han. and Chu. 2011. Cloud Performance: This subcategory covers articles focusing on the evaluation and optimisation of the performance of the clouds. In addition. distributed data processing in the clouds. 2009. and Buyya. and Maeng. Liu. the data centres. This classification is an upgraded version of that presented in a previous. Wang. Wu. et al. as shown in Table 2. Katz. Data Centre Management: This subcategory looks into the foundational enabler of cloud computing. discovering. Novel studies also look into component-based approaches for developing composite applications [Malawski. data redundancy [Pamies–Juarez. This grouping is based on assigning the single most applicable topic-category to a group of related subcategories (e. 2011] and automation in restructuring traditional applications into distributed/partitioned cloud-based ones [Böhm and Kanne. Gu. 2010]. Lin and Deng. Meng. 2009]. to enhance workflow scheduling and load balancing [Byun. 2008a. Johnson. Giuliani. Yan. we sought relationships between our initial categories (axial coding) and reduced the codes we initially identified into our final set of twenty-one subcategories [Strauss and Corbin. Paulson. we are able to offer a simplified and structured classification of the major categories and subcategories within current cloud computing research and conceptualise the relationships between these categories. Thus the 205 articles were full-text reviewed and eventually grouped into four broad categories: Technological Issues. Articles in this category concentrate on energy efficiency. and parallel RDBMS (Relational Database Management Systems) [Stonebraker. to specific analyses of particular cloud-based programming frameworks such as MapReduce [Liu. a classification framework. 2011. Sánchez–Artigas. and to improve interoperability across different clouds. data mining algorithms and methods [Grossman. 2010.g. and Wang. integration of distributed data [Chen. Six categories are related to technological issues. Articles in this subcategory range from generic discussions on developing distributed and parallel software in cloud computing environments [Lawton. Jiang. and Zheng. Business Issues. 5. 2011. Lee. and Hammoud. Talbi. Kee. Each subtopic was assigned to individual articles according to the articles’ spec ific research interest. 2011]. Pavio. Shi. Abawajy. Dang. to enable automatic bottleneck detection [Iqbal. 2010]. Meizner. related study [Yang and Tate. Kim.
Volume 31 42
Article 2
. and selecting cloud-based services [Goscinski and Brock. and Zhang.. 2010. 2009] and publishing. 2011]. 2010]. the twenty-one subcategories were grouped further into four top level topics using affinity analysis. This includes studies that attempt to quantify and compare performance across different clouds [Iosup et al. 2009]. Louridas. by assigning each article to only one primary subcategory.. ‘Data Management’. 2011].. 2006]. The K-J method (also called affinity diagramming) developed by Jiro Kawakita provides a systematic way to evaluate and agree on classifications [American_Society_for_Quality. Kong. These high-level categories were further validated by comparison with the high-level categories in the influential classification scheme for IS keywords [Barki. 2011]. 2011]. 3. 4. Wang. Abadi. Service Management: As an emerging research theme focusing on the administration of cloud computing services. to estimate performance of cloud network with nodes failure [Lin and Chang.

2010]. Yang. 2009]. Xiang. 2010]. Liu. Security: Cloud security has been a common concern for the public [Bellovin. Hu. A common approach for studying this topic is to compare different pricing strategies and analyse the pros and cons in terms of acceptance of customers. With rapid advancement in technology. and Hegarty. and Wray. governance. and a modelling tool for making buy-
Volume 31
Article 2
43
. when making decisions about cloud computing deployment. Education. Chu. 1. 2010]. Zhou. Wang. Huai. Liu. Kirschnick. It contains articles which propose that IT professionals. 2011]. 2009] and public auditability [Wang. 2011]. Articles in this category treat cloud computing as a black-box technology which can generate business value to both providers and users. 2010]. Legal Issues. Legal Issues: This subcategory examines legal issues associated with cloud computing. techniques to estimate and monitor costs for cloud services [Truong and Dustdar. Deontologist. privacy is an inevitable concern. and Buyya. Edwards. 2010]. as the cloud users have to upload and store (in some cases sensitive) business and personal information into remote data centres managed by external parties [Katzan. and Chen. Mobile Computing. and Li. Trust. Privacy.. Data Management. Trust: This subcategory examines approaches for cloud providers to gain trust from prospective users. Wang. Privacy: This subcategory specifically addresses privacy issues from either an ethical or legal point of view. In addition. and Westphall. and cloud-based security services [Li. Pricing: Articles in this subcategory mainly focus on the pricing strategies of cloud providers. Predictions Computing Domains and e-Science. 2010]. and Eccles. 2009]. 2010c]. 2010]. Seven categories have emerged in this category. and law [Kaufman. Ren. Adoption: This subcategory explores topics related to cloud-computing adoption in businesses. should consider applied ethics methods such as Utilitarian. B: Business Issues: This category concerns the business implications of cloud computing. Haggerty. 2009]. and cloudlevel defence against HTTP-DoS and XML-Dos attacks [Chonka. or between piece-rate pricing and flat-rate pricing [Li. 2. Gresty. as well as addressing specific topics such as digital forensic investigation in cloud computing systems [Taylor. 2011]. 2010] and argue that cloud providers need to display clear policies about how user data is used [Ryan. and software watermarking for multi-way authentications [Hwang and Li. 5. Wilcock. 6. 2009]. Data Centre Management. The data security category includes papers looking at data encryption [Anthes. 7. Topics in this category include a comparison between the cost of leasing cloud services and that of purchasing and using a local server cluster [Walker. Li. third-party assurance [Zissis and Lekkas. Venugopal. and more specific ones such as analysing operational costs for hosting online games in the cloud [Iosup. Wo. and a data-partitioning scheme for implicit security [Parakh and Kak. and Bonti. With cloud computing. Software Development. Ethical Issues. Open Source. and Li. 2010] and uncertain jurisdiction for Internet activities in geographically distributed cloud data centres [Ward and Sipior. 2011]. 2010]. 2011]. Lou. an instrument for evaluating the transparency of a cloud provider is proposed [Pauley. 2011]. 2011]. Applications Other Domains Topics Technological Issues 6. Adoption Conceptualising Cloud Foundational/Introductions. 2010]. Pricing. 2011]. Other articles addressing specific cloud related security issues fall into two categories: data security and network security. Cost: This subcategory examines the economic benefit from a cloud-user perspective. 4. and Rawlsian [Miller. 3. 2010]. Articles in this category identified two factors affecting trust in the cloud ―transparency [Bret. et al. Security Business Issues Cost. algorithms for finding minimum cost storage strategy [Yuan.Table 2: Classification of Topics in Cloud Computing Subtopics Cloud Performance. Baker. data colouring. The network security category includes papers discussing intrusion detection in the cloud [Vieira. Articles in this category introduce general legal risks of adopting cloud computing [Joint. Articles in this subcategory propose a method for analysing privacy in cloud computing in the workplace [Barnhill. 2011a. 2009]. Ren. Nae. Lou. e-Government. Some articles in this subcategory look at general security mechanisms such as restrictions and audits [Spring. Comparisons can be made between fixed prices and variable prices [Yeo. Ethical Issues: This subcategory analyses the cloud computing phenomenon from an ethical standpoint. regulators are often in a ‘catch-up’ mode with regard to policy. multi-tenancy authorisation [Calero. Schulter. Some articles in this category target general businesses by providing ROI (Return on Investment) models for firms to decide on the suitability of adopting cloud computing [Misra and Mondal. 2010]. Service Management. and Prodan.

O’Rourke. such as those for elearning [Doelitzscher. earth science. 2010].. Governments are more hesitant than businesses to adopt cloud computing services. C: Conceptualising Cloud Computing: This category contains articles that provide a general view of cloud computing practice and research. 2009]. et al. Voorsluys. However. 2008]. and Romney. with an aim to provide a general understanding of this area rather than to focus on any specific facet of it. and Wilson. Yang. Yuan et al. Shiers. Zhang. Foundational/Introductions: This subcategory contains articles that introduce foundational concepts and components of cloud computing.e. the CREN Large Hadron Collider) need to be processed in a timely manner. and even electricity [Brynjolfsson. 2009]. 2009. utilising cloud computing for electronic voting solutions has been argued to be beneficial and feasible [Zissis and Lekkas. 4. Mobile Computing: This subcategory contemplates the potential of combining cloud computing and mobile technologies [Zhang. To further articulate the essence of the cloud computing paradigm. Jones. 2011]. 2010]. strengths and weaknesses of cloud computing and suggest future research directions [Armbrust. Articles in this category discuss how a variety of educational areas can benefit from cloud computing. 2009]. 2009. reflect the timeline of cloud computing [Pallis. 2010]. while others speculate the economic prospects of cloud computing for developing nations [Greengard and Kshetri. as well as across public cloud providers. Li. et al. as well as on HPC (High Performance Computing) systems [Sterling and Stark. 2010]. 2009]. mobile phones. Robert. while others propose generic solutions for managing scientific workflow in the cloud [Yuan.. 2. Katzan. Joseph.e. some argue that by adopting cloud-based solutions. 2010]. 2010]. 3. Marston. 2011]. Katz.. and Google [Buyya. hence. as well as the benefits of adoption. Some project the technical and managerial effects of cloud computing on network and software vendors [Cusumano. etc. particle physics. which has long been yearning for infinite computing power. 2011] and enablers of the adoption of cloud computing [Yogesh and Navonil. Reich. online library resources [Jordan. 2009]. and Gibbs. Mell and Grance. Predictions: This subcategory contains articles focusing on forecasting the future of cloud computing and suggesting potential implications. and Jordan. such as enhanced competitive advantages [Truong. Kunjithapatham. et al. Blau. Konwinski. 2. 2009]. 2010]. Brisken. 2011]. Articles in this category have fairly specific focuses. 2008] and the inevitable adoption of cloud computing driven by NetGens 2. 2010]. Jeong. Some look into specific processing of genomic and proteomic data [May. and Wolf. especially those in the higher education sector. and sensors [Pandey. Some articles analyse more generic issues such as the influence of cloud computing on the job roles of IT staff in higher education [Currie. Yacef. 2010]. 2010b. virtual computing [Cervone.. One of the reasons for this is the associated risks and security concerns [Paquette. They are further classified into six subcategories. such money could be saved and used in places more meaningful to the students and teachers [Ercan. 2011]. bio-informatics. 2010. such as implementing a health-monitoring system based on a combination of cloud infrastructure.) where rapidly increasing volumes of data gathered from sensors and instruments (i. e-Government: This subcategory discusses the potential of cloud computing for governments. and Stosser. Microsoft. 1. Sulistio. and Buyya. and online collaborative writing [Calvo. D: Domains and Applications: This category consists of articles which discuss the impact of cloud computing on particular domains or applications. Weinhardt. Cloud computing. analyse the related benefits and obstacles. Kshetri. some articles make comparisons between cloud computing and other concepts such as grid computing [Buyya et al. 2011]. 2011. Fox. with its tremendous computing power and inexpensive cost..0 students who are born digital natives and rely on cloud-based applications for their life and study [Brown. 2010. 2010]. 2011] or proposing a ’virtualised screen‘ which is rendered in the cloud and presented on the mobile phone for enabling graphically
Volume 31 44
Article 2
. 1. e-Science refers to the scientific disciplines (i. e-Science: This subcategory targets the implications of cloud computing for the e-Science community. Hofmann. 2011]. Liu.or-lease storage decisions [Walker. Comparisons are also made between public cloud and private cloud [Grossman. These articles can be further classified into two subcategories. Operating and maintaining IT infrastructure has cost universities enormous amounts of money. 2011]. 2010]. Bandyopadhyay. such as Amazon. et al. Other articles focus more on SMEs (Small and Medium Sized Enterprises) and look into inhibitors [Truong and Dustdar. Khandoker. has drawn considerable attention from the e-Science community which has traditionally relied on scientific and academic computing grids. 2009]. cluster computing [Buyya. Jaeger. Griffith. Anandasivam. Vouk. 2010. and Reimann. Articles in this subcategory aim at understanding the impact of cloud computing on the current computing infrastructure of e-Science [Armando. Education: This subcategory focuses on the impact of cloud computing on educational institutes. 2010. Niu. Such introductory articles provide definitions and outline key features of cloud computing [Armbrust. 2010.. Kuijs. and Ghalsasi. and Chen.

Figure 3. et al. Chen. RESULTS AND ANALYSIS
A total of 205 articles were classified according to our scheme. 2009]. As previously mentioned. cloud platforms should be built on open standards.
IV. However the small number of papers regarding business issues indicates a lack of business perspective in cloud computing research. such as data security. 2008] for reducing the implementation cost of RFID solutions [Owunwanne and Goel. This may be because the value and implications of cloud computing are still under-recognised in business disciplines. The results of the classification are presented next. whereas the security concern has long been a most cited reason for users to object to cloud
Volume 31
Article 2
45
.. 23 percent). and open source software [Nelson. 2010. ‘Cloud Performance’ (thirty articles. Granger. 2011]. Llorente. we can predict the total number for that year will easily exceed that of 2010.. This review takes a descriptive approach. followed by ‘Conceptualising Cloud Computing’ (forty-eight articles. primary contribution. and for developing intelligent urban transportation systems [Li. 6. Total Number of Articles per Year As shown in Figure 3. and Shen. 14 percent). 2011]. but journal publications were sporadic until 2008. and the publication outlets. Heath. while the least published category was ‘Business Issues’ (twenty-eight articles. the term ‘cloud computing’ was coined by industry practitioners in 2006. such as Open Nebula [Milojicic. We also analysed the articles by year of publication. 2010]. Considering the 2011 figure represents only half a year. data integrity. and Wang. Open Source: This subcategory looks into merging the two paradigms ―cloud computing and open source ―to build open clouds. Berl et al. 2010]. 5. Clearly. 2010]. from 2008 to 2010 the number of peer-reviewed journal articles has increased substantially. The key theme is the proposal that to ensure that the Internet becomes an interoperable ‘network of networks’. This is unsurprising. Li. as well as arguing that migrating computing and storage capability to the cloud not only enhances the power of mobile systems but also extends the battery lifetimes of such systems [Kumar and Lu. and Montero. This explosive growth of journal publications reflects academia’s increasing acceptance of cloud computing as a salient and legitimate research area. for building smaller. Performance improvement has always been an important reason for users to adopt cloud computing. 34 percent) and ‘Security’ (twenty-nine articles. and smarter robots [Guizzo. Campbell. Topics include using cloud computing for improving analysing and reasoning capabilities of semantic search engines [Mika and Tummarello.rich services on thin clients [Lu. We provide an overview of the current developments in cloud computing research by conducting a systematic literature classification using the classification scheme presented above.. energy efficiency.
Distributions of Articles by Topics
‘Technological Issues’ clearly stands out as the most heavily published research category ( eighty-eight articles. Table 3 lists the number of articles for each subcategory under technological issues. 2011]. Academic researchers started to engage with this trend in late 2007. Gupta. open interface. In addition. 20 percent). Ko. some emerging open cloud platforms are introduced. Other Domains: This subcategory contains articles which each represent a stand-alone topic relevant to the application of cloud computing.
Distribution of the Articles by Year
No articles related to ‘cloud computing’ were published before 2007 because no studies exist under this name. research methods. and there are still many technological obstacles for the growth of cloud computing. 2011] and Open Cirrus [Avetisyan. cheaper. and ‘Domains and Applications’ (forty-one articles. 33 percent) are two major issues in cloud computing research. 2010]. and performance predictability [Armbrust et al. 43 percent). Technical issues are important.

Trustbuilding in cloud computing has recently gained traction due to organisations’ resistance and doubts regarding the rapidly increasing range of cloud providers. 49 percent). It is unsurprising to see that thirty-six articles.computing [Armbrust et al. especially higher education. Hence studies in this direction often take a cloud provider’s standpoint and look for effective approaches to establish consumers’ trust towards cloud services. Topics in this category are treated more evenly than those in the ‘Technological Issues’ category. 9 percent). ‘Privacy’ and ‘Legal Issues’ (each five articles. ‘Service Management’ (four articles. ‘Data Management’ (ten articles. Therefore. ‘Cost’ and ‘Trust’ (each four articles. and improvement of the cloud performance are of great interest to the researchers. Table 6 shows the number of articles classified as ‘Domains and Applications’. and architectures for strengthening security are also popular. 11 percent) seems to be more popular than ‘Software Development’ (eight articles. 2010]. but is expected to grow. evaluating and assessing the suitability of adopting cloud computing has attracted interest. Almost half the articles in thi s category are concerned with ‘Education’ (twenty articles.. After all. the biggest group across all categories. but only some of them will develop and deploy applications over there. the measurement. they are often analysed from the cloud consumer’s perspective [Svantesson and Clarke. Cloud computing is not a panacea and not suitable for every organisation. Articles in the ‘Predictions’ subcategory account for only one third of all articles in this area. It is a bit surprising to see ‘ e-Science’ (six articles. and the future may see more universities collaborating with cloud providers. These two have become major risks perceived by businesses when migrating to the cloud. 18 percent) are both ranked in second place. This echoes the trend that most organisations have refocused on cost efficiency with regard to IT investment under the current economic downturn. Similarly. 21 percent) is the most discussed topic according to our classification. ‘Pricing’ and ‘Ethical Issues’ (each two articles. Table 3: Number of ‘Technological Issues’ Articles Technological Issues Number of articles Cloud Performance 30 (34%) Security 29 (33%) Data Management 10 (11%) Software Development 8 (9%) Data Centre Management 7 (8%) Service Management 4 (5%) Total 88 (100%) Note: The percentage figures are rounded. 14 percent) are jointly ranked third. mechanisms. Hence. Cost-saving may be the strongest incentive for many organisations to look into cloud computing. cloud computing is still a fresh paradigm which needs more time to be well-conceptualised. assessment. 2010]. ‘Adoption’ (six articles. Table 4: Number of ‘Business Issues’ Articles Business Issues Number of articles Adoption 6 (21%) Privacy 5 (18%) Legal Issues 5 (18%) Cost 4 (14%) Trust 4 (14%) Pricing 2 (7%) Ethical Issues 2 (7%) Total 28 (100%) Note: The percentage figures are rounded. These articles provide general introductions of foundational concepts and overviews of cloud computing. 7 percent) are the least researched. algorithms. Table 5 shows the number of articles in the ‘Conceptualising Cloud Computing’ category. This indicates that the potential of cloud computing has been consciously envisaged and analysed by educators. but both are emerging topics in cloud computing research and may gain more attention in the future. Table 4 shows the number of articles in topics related to business issues. hence. along with the increasing popularity of research in ‘service science’ and ‘service orientation’. 15
Volume 31 46
Article 2
. this might be due to the fact that all cloud computing consumers need to store data in the cloud in whatever form. are in the ‘Foundational/Introductions’ subcategory. 5 percent) is currently the least researched topic in this area. Evaluating and quantifying explicit and implicit costs of cloud computing services is very pertinent for those organisations which are planning to adopt cloud computing with a view to cost-saving.

70 percent) come from twenty journals (as shown in Table 7). That ‘e-Government’ (two articles. this is merely a proposal but later it may provoke a shift in the industry. Given the hunger for computing power in e-Science communities. publications 16 15 14 14 13 13 9 7 7 7 5 4 4 3 3 2 2 2 2 2 144
Volume 31
Article 2
47
.Table 5: Number of ‘Conceptualising Cloud Computing’ Articles Conceptualising Cloud Computing Number of articles Foundational/Introductions 36 (75%) Predictions 12 (25%) Total 48 (100%) Note: The percentage figures are rounded. This is understandable as cloud computing research is still an immature area requiring better conceptualisation. ISR. 10 percent) is also an area worth watching. 5 percent) comes last represents the conservative attitude of most governments towards cloud computing. Table 6: Number of ‘Domains and Applications’ Articles Applications Number of articles Education 20 (49%) e-Science 6 (15%) Mobile Computing 5 (12%) Open Source 4 (10%) e-Government 2 (5%) Other 4 (10%) Total 41 (100%) Note: The percentage figures are rounded. Table 7 is a helpful resource for researchers wanting to publish cloud computing studies or for anyone looking for good quality cloud-computing references. one could expect them to show more enthusiasm towards cloud computing.
Publication Outlets
The publication outlets of the articles were also analysed. Table 7: Distribution of Articles by Journals (Top 20)
Journal Future Generation Computer Systems IEEE Security & Privacy Communications of the ACM IEEE Internet Computing Computer IT Professional EDUCAUSE Review Journal of Network and Computer Applications Journal of Parallel and Distributed Computing Procedia Computer Science IEEE Spectrum Computing. and EJIS. The majority of the articles (144 articles. Currently. theory-oriented IS journals such as MISQ. Clearly cloud computing-related articles have not appeared yet in most of the top. Though ‘Mobile Computing’ (five articles. Open source communities are pushing cloud computing towards open standards. this topic is becoming increasingly popular and the combined future of mobile devices and cloud infrastructures is not to be underestimated. percent) lagging behind higher education. 12 percent) is in third place in this classification. It is not clear yet to what extent the new and changed affordances emerging from cloud computing technologies require theory-building and new theoretical explanations. IEEE Transactions on Journal of Systems and Software Computer Law & Security Review International Journal of Management and Information Systems International Journal of Information Management Computing in Science & Engineering Expert Systems with Applications Journal of Enterprise Information Management Total No. Archives for Informatics and Numerical Computation Parallel and Distributed Systems. ‘Open Source’ (four articles.

and avoiding much nonproductive system administration work [Lawton.g. ‘adoption’ has become a fundamental theme among the business oriented articles. Adoption of cloud computing is a major concern in our practitioner community. even when the topics of the articles (e. However. security. digest the knowledge. once they have stabilised. In the first five months of 2011. Second. Though the
Volume 31 48 Article 2
. most studies focus on praxis. Producing strong research results related to praxis may be a natural way to strengthen the legitimacy of this research area. testing and releasing their products more quickly. there is an obvious need for more research in the ‘Business Issues’ category from both cloud providers’ perspective and cloud consumers’ perspective. and in our view there is an urgent demand for articles explaining cloud computing technologies in business-friendly language. relevance to praxis can and should be placed at the centre [Lyytinen and King. Given that cloud computing potentially represents a ‘paradigm shift’ in IT delivery methods.g. many traditional IT management issues with high practical relevance deserve rigorous academic re-examination in the cloud-computing context. the number of research articles has been increasing dramatically every year since 2008. According to our review. trust. 2006]. This is consistent with the trend in other nascent research areas.V. but only with the benefit of hindsight. The results presented in this article have suggested useful insights to both business and academic researchers. First. our review indicates that theory-building is still not at the centre of cloud computing research. this number has already approached that of the whole of 2010. Cloud computing clearly has salience. As we discussed. even though our literature analysis has revealed that technology-focused articles outnumbered businessfocused ones. Instead. such as mobile business [Scornavacca. data management) are highly relevant to business interests. cost. Finally. Early business applications are frequently experimental. The IT management implications of deploying PaaS may affect aspects of system testing and implementation phases. This is because of a traditional view that the academic legitimacy of a research field hinges on the presence or absence of core theories. These questions could include: How does cloud computing impact current practices of IT management and governance? Does cloud computing improve IT business alignment and IT agility? What are the critical factors of a successful business model with cloud computing? Mainstream IS journals could encourage discussions and investigations in these areas. new technologies need to be robust before they can be widely adopted for mission-critical applications. and IaaS) identified by the NIST all have distinct business implications. The lack of solid theoretical foundations has long been a concern for IS academics. It would be interesting to explore whether there is a ‘research cycle’ associated with the emergence and widespread commercialisation of new technology affordances and innovations. Existing articles in the ‘Technological Issues’ category focus mostly on specific technical details which are often ad dressed from cloud computing technical specialists’ standpoint. Barnes. The three service layers (SaaS. However. Third. DISCUSSION
The intention of this article is to illustrate a landscape of current academic research from an IS standpoint. in our view. and disruptive changes in business models are not always apparent as they are occurring. As the economic downturn is fuelling interest in cloud computing. 2008a]. However. but have little impact on the design and development phases. not merely to report and explain their occurrence after the event. For instance. These articles may be informative but do not offer much practical or applicable knowledge to business professionals who are on the user side of cloud computing. Further research should acknowledge the differences across the three service layers and explore the implications for businesses in a more nuanced manner. We have presented a descriptive review. there is no doubt that more researchers will engage with this topic. All the other subtopics (e. Salience and strong results should be major determinants of the academic legitimacy of the IS research field. PaaS. the research community should be ready to critically examine these issues. Existing articles in this category tend to take a ‘black -box’ approach when studying cloud computing and fail to make nuanced distinctions between different service layers and deployment models of cloud computing. It is difficult to predict whether the widespread availability of computing ‘on demand’ will significantly alter the patterns of adoption and diffusion of new computing innovations and result in new business models. classifying the literature of extant cloud computing research in a range of categories. there are many other research opportunities beyond ‘adoption’ for IS scholars interested in cloud computing. Lyytinen and King have recently argued that to increase the legitimacy of an ‘applied research’ field like IS. cloud performance. adopting PaaS can facilitate the processes of IS development (ISD) by enabling developers to collaborate globally. these articles do not meet the challenge made by Robey and Markus [1998] more than ten years ago to produce more consumable research. and whether research in cloud computing is following a similar pattern to that of other major technology innovations. it will not necessarily assist with the changes in application and database that require the intervention of IT professionals. However. and envisage the implications to business strategies and practices. In general we expect an exponential growth in the amount of cloud computing research in the near future. Business users may find it extremely difficult to read these articles. and Huff. privacy) under the ‘Business Issues’ category contribute in varying degrees to the decision making process for adopting cloud services. 2004].

CONCLUSION
Practitioner and academic interest in the evolving phenomenon of cloud computing is intense. A. 2669– 2677. Will cloud computing help to mitigate the IS management problems typically experienced by small. 3. not AIS.. F. The author(s) of this article. 1998]. the classification scheme might not reflect the topic distribution of conference papers related to cloud computing. R. can gain direct access to these linked references. If yes. we see it as a positive trend for IS researchers that a wide variety of publication outlets have started accepting research on cloud computing. Therefore. http://asq. our search criteria might be incomplete.
VII. IS researchers may be able to help the decision making of enterprises regarding cloud computing adoption and innovation. however.procs.and medium-sized enterprises (SMEs)? Do the affordances of cloud computing help achieve increased IT agility in large organisations? These questions are interesting and highly salient. Our classification and descriptive review can provide a useful quality reference source for academics and practitioners with an interest in cloud computing. The global recession is forcing the IT functions of organisations to focus on cost saving and resource efficiency. M.classification framework provided in this article helps to structure the process.” Communications of the ACM (53)11. 406. Procedia Computer Science (1)1. (2011) “Cloud Computing―What’s in It for Me as a Scientist?” Science (331)6016. conducting a similar literature analysis will be increasingly challenging due to the sheer volume of articles being published. Readers who have the ability to access the Web directly from their word processor or are reading the article on the Web. This may hinder the ability of the present article to present a complete picture of the current developments in this domain. many quality professional articles may also embrace this phenomenon. 16. as some papers discussing cloud computing that do not have the term ‘cloud computing’ in the abstract or keyword list may not have been included.2010. which are promised as major benefits of cloud computing. pp. it provides insights into the current state of cloud computing research. Third. is (are) responsible for the accuracy of their content. Second.
VI. what aspects should be considered when choosing a cloud provider? What criteria can be used to make a comparison across the different cloud services? This might be informed by insights from IT outsourcing literature. J. the articles included are all refereed journal articles. p. Anthes. We suggest that IS researchers could consider the following questions: Should an enterprise adopt cloud computing and when? This could be investigated from the point of view of IS strategy and organisational diffusion of innovation. LIMITATIONS
This article has a number of limitations. Where version information is provided in the References.html (current June 20. is (are) responsible for the accuracy of the URL and version information. and suggestions for future lines of research that will have strong salience to our practitioner community. First. Readers are warned. (2010) “Security in the Cloud.04. However. The author(s) of the Web pages.1016/j. Cloud computing has displayed huge potential for IS researchers to produce ‘consumable research‘ [Robey and Markus. American_Society_for_Quality (2006) “Idea Creation Tools―Affinity Diagrams. We are expecting to see more cloud computing articles published in leading IS journals. 2011). Armando.300. our sample was mainly based on academic publications. Crespo. Anguita. different versions may not contain the information or the conclusions referenced. The contents of Web pages may change over time. Alonso–Calvo. As cloud computing is industry-driven in nature. Maojo (2010) “On Distributing Load in Cloud Computing: A Real Application for Very-large Image Datasets”. Although this review cannot claim to be exhaustive.” quality/idea-creation-tools/overview/affinity. 2. These links existed as of the date of publication but are not guaranteed to be working thereafter. doi: 10.
REFERENCES
Editor’s Note: The following reference list contains hyperlinks to World Wide Web pages. not AIS. that: 1. Garc'ia–Remesal. and V. By investigating these questions. G. 4. this study contributes to our understanding of how research into the business applications of new technologies develops.org/learn-about-
Volume 31
Article 2
49
.
ACKNOWLEDGMENTS
We gratefully acknowledge the mentoring provided by Professor Sid Huff and the careful manuscript editing carried out by Sarah Johnstone. p. Also.

Thomas Vance Wilson Worcester Polytechnic Institute
CAIS EDITORIAL BOARD
Monica Adya Marquette University Andrew Gemino Simon Fraser University Douglas Havelka Miami University Julie Kendall Rutgers University Claudia Loebbecke University of Cologne Shan Ling Pan National University of Singapore Raj Sharman State University of New York at Buffalo Padmal Vitharana Syracuse University Yajiong Xue East Carolina University
DEPARTMENTS
Information Systems and Healthcare Editor: Vance Wilson James P. Joshi Washington State University Nelson King American University of Beirut Paul Benjamin Lowry City University of Hong Kong Katia Passerini New Jersey Institute of Technology Mikko Siponen University of Oulu Rolf Wigand University of Arkansas.D. Little Rock Indranil Bose Indian Institute of Management Calcutta Mary Granger George Washington University Michel Kalika University of Paris Dauphine Hope Koch Baylor University Don McCubbrey University of Denver Jan Recker Queensland University of Technology Thompson Teo National University of Singapore Fons Wijnhoven University of Twente Thomas Case Georgia Southern University Åke Gronlund University of Umea Karlheinz Kautz Copenhagen Business School Nancy Lankton Marshall University Fred Niederman St. ISSN: 1529-3181
EDITOR-IN-CHIEF Matti Rossi Aalto University AIS PUBLICATIONS COMMITTEE
Kalle Lyytinen Vice President Publications Case Western Reserve University Robert Zmud AIS Region 1 Representative University of Oklahoma Matti Rossi Editor. Inc. CAIS Aalto University Phillip Ein-Dor AIS Region 2 Representative Tel-Aviv University Shirley Gregor Editor. Tinsley AIS Executive Director Information Technology and Systems Editors: Dinesh Batra and Andrew Gemino Sheri Hronek CAIS Publications Editor Hronek Associates. Lynne Markus Bentley University Ralph Sprague University of Hawaii
CAIS SENIOR EDITORS
Steve Alter University of San Francisco Michel Avital Copenhagen Business School Dinesh Batra Florida International University Matt Germonprez University of WisconsinEau Claire K. Watson University of Georgia
CAIS ADVISORY BOARD
Gordon Davis University of Minnesota Jay Nunamaker University of Arizona Ken Kraemer University of California at Irvine Henk Sol University of Groningen M. JAIS The Australian National University Bernard Tan AIS Region 3 Representative National University of Singapore Richard Mason Southern Methodist University Hugh J. Papers in French Editor: Michel Kalika Copyediting by S4Carlisle Publishing Services
ADMINISTRATIVE PERSONNEL
Meri Kuikka CAIS Managing Editor Aalto University
Volume 31
Article 2
.. Louis University Jackie Rees Purdue University Chelley Vician University of St.

download. users may print.Copyright of Communications of AIS is the property of Association for Information Systems and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission.
. or email articles for individual use. However.